Literature review on optimization of transboundary water for irrigation DOI Creative Commons
Entin Hidayah, Retno Utami Agung Wiyono, Wiwik Yunarni Widiarti

и другие.

Water Science & Technology Water Supply, Год журнала: 2024, Номер 24(12), С. 3979 - 4008

Опубликована: Ноя. 11, 2024

ABSTRACT Transboundary water resources are essential for agricultural sustainability and regional development, they intrinsically linked to achieving the United Nations' SDGs water-food-energy nexus (WFE-NEXUS) concept. Despite challenges such as conflicting allocation climate change impacts, effective transboundary management irrigation is crucial meeting of eradicating hunger, providing clean sanitation, offering affordable sustainable energy, taking action. This work synthesizes approaches optimization, highlighting significance a holistic plan that considers both technical social factors. Remote-sensing technologies, data forecasting, hydrology hydraulic modelling, resource modelling all contribute maximize policy creation, particularly when paired with collaborative government features. integrated approach optimization fosters long-term development by improving livelihoods, resilience, inclusive growth through efficient management.

Язык: Английский

Future groundwater potential mapping using machine learning algorithms and climate change scenarios in Bangladesh DOI Creative Commons
Showmitra Kumar Sarkar, Rhyme Rubayet Rudra,

Swapan Talukdar

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Май 6, 2024

Abstract The aim of the study was to estimate future groundwater potential zones based on machine learning algorithms and climate change scenarios. Fourteen parameters (i.e., curvature, drainage density, slope, roughness, rainfall, temperature, relative humidity, lineament land use cover, general soil types, geology, geomorphology, topographic position index (TPI), wetness (TWI)) were used in developing algorithms. Three artificial neural network (ANN), logistic model tree (LMT), regression (LR)) applied identify zones. best-fit selected ROC curve. Representative concentration pathways (RCP) 2.5, 4.5, 6.0, 8.5 scenarios precipitation for modeling change. Finally, identified 2025, 2030, 2035, 2040 best RCP models. According findings, ANN shows better accuracy than other two models (AUC: 0.875). predicted that 23.10 percent very high zones, whereas 33.50 extremely forecasts values under different (RCP2.6, RCP4.5, RCP6, RCP8.5) using an spatial distribution maps each scenario. sixteen generated Government officials may utilize study’s results inform evidence-based choices water management planning at national level.

Язык: Английский

Процитировано

5

Spatial Mapping and Prediction of Groundwater Quality Using Ensemble Learning Models and SHapley Additive exPlanations with Spatial Uncertainty Analysis DOI Open Access
Shilong Yang,

Danyuan Luo,

Jiayao Tan

и другие.

Water, Год журнала: 2024, Номер 16(17), С. 2375 - 2375

Опубликована: Авг. 24, 2024

The spatial mapping and prediction of groundwater quality (GWQ) is important for sustainable management, but several research gaps remain unexplored, including the inaccuracy interpolation, limited consideration geological environment human activity effects, limitation to specific pollutants, unsystematic indicator selection. This study utilized entropy-weighted water index (EWQI), LightGBM model, pressure-state-response (PSR) framework SHapley Additive exPlanations (SHAP) analysis address above gaps. normalized importance (NI) shows that NO3− (0.208), Mg2+ (0.143), SO42− (0.110), Cr6+ (0.109) Na+ (0.095) should be prioritized as parameters remediation, skewness EWQI distribution indicates although most sampled locations have acceptable GWQ, a few areas suffer from severely poor GWQ. PSR identifies 13 indicators environments activities SMP Despite high AUROCs (0.9074, 0.8981, 0.8885, 0.9043) across four random training testing sets, it was surprising significant uncertainty observed, with Pearson correlation coefficients (PCCs) 0.5365 0.8066. We addressed this issue by using spatial-grid average probabilities maps. Additionally, population nighttime light are key indicators, while net recharge, land use cover (LULC), degree urbanization lowest importance. SHAP highlights both positive negative impacts on identifying point-source pollution main cause GWQ in area. Due field, future studies focus six aspects: multi-method assessment, quantitative relationships between comparisons various models, application selection, development methods reduce uncertainty, explainable machine learning techniques management.

Язык: Английский

Процитировано

4

Unleashing the Untapped Potential: Groundwater Exploration in a Watershed Environment of North‐East India Using MCDAAHP Techniques DOI Open Access
Debashree Borah,

Ashok Kumar Bora

Hydrological Processes, Год журнала: 2025, Номер 39(1)

Опубликована: Янв. 1, 2025

ABSTRACT The contemporary era is marked by the faster exploitation of groundwater resources due to combined effects burgeoning population and rapid industrialisation. This study tries delineate potential zones (GWPZs) in a fragile agriculturally dominant watershed North‐East India using GIS‐based multi‐criteria decision analysis (MCDA) approach Analytical Hierarchy Process (AHP) technique. has undertaken 10 influencing factors: geomorphology, geology, land use/land cover (LU/LC), drainage density, rainfall, soil texture, slope, lineament topographic wetness index (TWI) normalised difference water (NDWI). Suitable weights for parameters are assigned according their relative importance association with storage based on pairwise comparison matrix (PCM). Four GWPZs respective coverages namely poor (3.39%), moderate (24.98%), good (33.36%) excellent (38.27%) categories found. central southern parts area covering portion Udalguri, Sonitpur Darrang districts Assam have porous geological settings floodplains, indicating high potentiality. In contrast, northern part hard rugged terrain lacks storage. Incorporating socio‐economic aspect, particularly number villages or without access suitable groundwater, significantly enhances study's utility. outcome cross‐verified well data obtained from Central Groundwater Board (CGWB) field which validated receiver operating characteristics (ROC) curve resulting an accuracy 72.9%. Hence, this inquiry implications both regional global significance will assist stakeholders authorities creating roadmap sustainable effective use.

Язык: Английский

Процитировано

0

Machine learning and CORDEX-Africa regional model for assessing the impact of climate change on the Gilgel Gibe Watershed, Ethiopia DOI
Amanuel Kumsa Bojer,

Muluneh Woldetsadik,

Bereket Hailu Biru

и другие.

Journal of Environmental Management, Год журнала: 2024, Номер 363, С. 121394 - 121394

Опубликована: Июнь 9, 2024

Язык: Английский

Процитировано

1

Literature review on optimization of transboundary water for irrigation DOI Creative Commons
Entin Hidayah, Retno Utami Agung Wiyono, Wiwik Yunarni Widiarti

и другие.

Water Science & Technology Water Supply, Год журнала: 2024, Номер 24(12), С. 3979 - 4008

Опубликована: Ноя. 11, 2024

ABSTRACT Transboundary water resources are essential for agricultural sustainability and regional development, they intrinsically linked to achieving the United Nations' SDGs water-food-energy nexus (WFE-NEXUS) concept. Despite challenges such as conflicting allocation climate change impacts, effective transboundary management irrigation is crucial meeting of eradicating hunger, providing clean sanitation, offering affordable sustainable energy, taking action. This work synthesizes approaches optimization, highlighting significance a holistic plan that considers both technical social factors. Remote-sensing technologies, data forecasting, hydrology hydraulic modelling, resource modelling all contribute maximize policy creation, particularly when paired with collaborative government features. integrated approach optimization fosters long-term development by improving livelihoods, resilience, inclusive growth through efficient management.

Язык: Английский

Процитировано

0